On Mon, Dec 15, 2014 at 6:27 PM, Anne Mulhern <amulhern@redhat.com> wrote:
Hi!
Pretend I have classes:
class A(object): pass
class B(object): pass
class C(A,B): pass
class D(object): pass
The MRO linearizations are:
L(object) = [object] L(A) = [A, object] L(B) = [B, object] L(C) = [C, A, B, object] L(D) = [D, object]
I'll say that L(X) > L(Y) if every c in L(Y) occurs in L(X). By that rule L(C) and L(D) are maximal linearizations.
I want to write an analysis which would work best if I could gather up all the linearization of all classes in a possibly large package distributed over possibly many files and find only the maximal linearizations.
This is really a kind of whole-program analysis.
I don't believe that this fits the pylint model very well, since it is reasonable to expect that pylint would be run separately on each individual file in a library.
Are there other analyses around that make use of astroid and are more whole-program like?
Thanks!
Hi, Anne. I'm currently working on adding mro support in astroid (need it to solve a false positive in Pylint). After this, it will be easy to use astroid for your task, by walking each file in your package, build an astroid.module with AstroidBuilder.file_build, get all the classes using Module.nodes_of_class and finally calling .mro for each one. I'll push the change to astroid tonight.